A magnetic resonance imaging (MRI) system generates images of a human body in, e.g., transversal, longitudinal and diagonal directions. By using these MRI images, a medical state of the human body can be inspected and diagnosed.
For the purposes of accurate diagnosis, various researches are being conducted to develop a method for acquiring images having high resolution and high contrast. Among them, a research using magnetic resonance electrical impedance tomography (MREIT) is attracting attention.
MREIT is a technique of generating an in vivo conductivity distribution image by applying a magnetic resonance pulse train to a living body while inputting an electric current into the living body from an external current source. MREIT is an application of electrical impedance tomography (EIT) to an MRI apparatus. With this MREIT technique, a change in conductivity can be easily detected at any parts of the living body, and a high-resolution image can be produced.
An imaging method using a spin echo pulse train as the magnetic resonance pulse train has been widely utilized in the conventional MREIT.
In this regard, in a MREIT review paper entitled “Magnetic Resonance Electrical Impedance Tomography (MREIT) for High-Resolution Conductivity Imaging” (Woo E J et al., Physiological Measurement, vol. 29, no. 10, pp. R1-R26, 2008), MREIT is introduced and analyzed.
The conventional MREIT, however, has drawbacks in that it takes time for spin magnetization recovery, and, thus, time required to acquire data for quantitative imaging of in vivo conductivity is very long. Further, in case of the conventional MREIT, since one-to-one linear relationship is established between an electric current inputted from the outside and a phase shift of a magnetic resonance image, phase sensitivity of the image to the external electric current is limited. Thus, a large quantity of electric current needs to be applied to acquire information on an induced magnetic flux density having a high signal-to-noise ratio (SNR), which raises safety issues.